R Notebook _ Data Splitting

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library(caret)

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set.seed(3456)
trainIndex <- createDataPartition(iris$Species, p = .8, 
                                  list = FALSE, 
                                  times = 1)
head(trainIndex)

     Resample1
[1,]         1
[2,]         2
[3,]         4
[4,]         5
[5,]         6
[6,]         8

library(mlbench)
data(BostonHousing)
testing <- scale(BostonHousing[, c("age", "nox")])
set.seed(5)
## A random sample of 5 data points
startSet <- sample(1:dim(testing)[1], 5)
samplePool <- testing[-startSet,]
start <- testing[startSet,]
newSamp <- maxDissim(start, samplePool, n = 20)
head(newSamp)

[1] 461 406  49 308 469  76